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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/28574

Title: Household members do not contact each other at random: implications for infectious disease modelling
Authors: Goeyvaerts, Nele
Santermans, Eva
Potter, Gail
Torneri, Andrea
Van Kerckhove, Kim
Willem, Lander
Aerts, Marc
Beutels, Philippe
Hens, Niel
Issue Date: 2018
Publisher: ROYAL SOC
Citation: PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 285(1893), (ART N° 20182201).
Abstract: Airborne infectious diseases such as influenza are primarily transmitted from human to human by means of social contacts, and thus easily spread within households. Epidemic models, used to gain insight into infectious disease spread and control, typically rely on the assumption of random mixing within households. Until now, there has been no direct empirical evidence to support this assumption. Here, we present the first social contact survey specifically designed to study contact networks within households. The survey was conducted in Belgium (Flanders and Brussels) from 2010 to 2011. We analysed data from 318 households totalling 1266 individuals with household sizes ranging from two to seven members. Exponential-family random graph models (ERGMs) were fitted to the within-household contact networks to reveal the processes driving contact between household members, both on weekdays and weekends. The ERGMs showed a high degree of clustering and, specifically on weekdays, decreasing connectedness with increasing household size. Furthermore, we found that the odds of a contact between older siblings and between father and child are smaller than for any other pair. The epidemic simulation results suggest that within-household contact density is the main driver of differences in epidemic spread between complete and empirical-based household contact networks. The homogeneous mixing assumption may therefore be an adequate characterization of the within-household contact structure for the purpose of epidemic simulations. However, ignoring the contact density when inferring based on an epidemic model will result in biased estimates of within-household transmission rates. Further research regarding the implementation of within-household contact networks in epidemic models is necessary.
Notes: [Goeyvaerts, Nele; Santermans, Eva; Van Kerckhove, Kim; Aerts, Marc; Hens, Niel] UHasselt, Interuniv Inst Biostat & Stat Bioinformat, Hasselt, Belgium. [Potter, Gail] Emmes Corp, Rockville, MD USA. [Torneri, Andrea; Willem, Lander; Beutels, Philippe; Hens, Niel] Univ Antwerp, Vaccine & Infect Dis Inst, Ctr Hlth Econ Res & Modelling Infect Dis, Antwerp, Belgium. [Goeyvaerts, Nele] Janssen Res & Dev, Beerse, Belgium.
URI: http://hdl.handle.net/1942/28574
DOI: 10.1098/rspb.2018.2201
ISI #: 000456873600010
ISSN: 0962-8452
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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